Accurate and efficient tracking of the as-built (or actual physical) status of structures being built has been repeatedly reported as a critical factor for success of project control. Such information directly supports progress monitoring and control and if automated can significantly impact management of a project. Despite the importance of progress monitoring, current methods for site data collection, processing and representation are time-consuming and labor-intensive. These methods call for manual data collection and extensive as-planned and as-built data extraction from structural drawings, schedules and daily construction (or build) reports produced by superintendents, subcontractors and trades foremen. Similar challenges arise in other fields of manufacture, including in the auto industry or other manufacturing industries.
Quality of the daily progress reports also highly depends on the data collected by field personnel which tends to be based on their interpretation of what needs to be measured, the way it needs to be measured and the way it needs to be presented, and therefore, it may not reveal the actual impact of site circumstances on the construction project. For example, on a daily construction report submitted by a drywall contractor, it may be reported that framing was conducted without specifying the amount of resources being used, the exact location of the work performed or the progress made. Even if progress is measured, it may be conducted in a non-systematic way and metrics may tend to be subjective. For example, a concrete subcontractor reports that 60% of the roof work is complete. This could mean 60% of the planned area/volume of concrete is placed, or that 60% of the planned labor-hours has been spent. Or, it may mean that 60% of the actual requirement has been completed. If the item being referenced is a small work unit, it may not have a significant difference. However, in the case where the references are to the whole task, assumption of input/output proportionality could be very misleading.
Finally, progress-monitoring reports are visually complex. Decision-making for corrective control actions and revision of work schedule typically takes place in contractor coordination meetings. A wide range of individuals with different areas of expertise and interests often attend these meetings. In these face-to-face interactions, progress information needs to be easily and quickly communicated among the participants. However, none of the existing reporting methods (e.g., progress S curves, schedule bar charts and the like) easily and effectively present multivariable information (e.g., schedule and performance) nor do they intuitively reflect information pertaining to the spatial aspects of progress and their associated complexities. Existing representations cause a significant amount of information to be inefficiently presented in coordination meetings. As a result, extra time is often spent in explaining the context in which problems occurred rather than understanding the causes of the problems, evaluating alternatives to solve the problems and discussing corrective actions. Accordingly, prior methods make it difficult and expensive to gather, analyze, and visualize construction progress monitoring data (e.g., actual progress or as-built, expected progress or plan, and their deviations), which needs to be easily and quickly shared among project stakeholders.